Model Assessment of Dynamical Atmospheric Pollution Control Schemes Based on Sensitive Source Zone Analysis

Xu Jing; Zhang Xiaoling; Cai Xuhui; Zhao Xiujuan; Su Jie; Zhang Ziyin; Wen Wei

doi:10.11898/1001-7313.20160602

Vol.27, NO.6, 2016

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Article Navigation > Journal of Applied Meteorological Science > 2016 > 27(6): 654-665

Xu Jing, Zhang Xiaoling, Cai Xuhui, et al. Model assessment of dynamical atmospheric pollution control schemes based on sensitive source zone analysis. J Appl Meteor Sci, 2016, 27(6): 654-665. DOI: 10.11898/1001-7313.20160602.

Citation:

Xu Jing, Zhang Xiaoling, Cai Xuhui, et al. Model assessment of dynamical atmospheric pollution control schemes based on sensitive source zone analysis. J Appl Meteor Sci, 2016, 27(6): 654-665. DOI: 10.11898/1001-7313.20160602.

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Model Assessment of Dynamical Atmospheric Pollution Control Schemes Based on Sensitive Source Zone Analysis

DOI: 10.11898/1001-7313.20160602

Xu Jing^1,2,
Zhang Xiaoling^{1,2
,
,},
Cai Xuhui³,
Zhao Xiujuan^1,2,
Su Jie^1,2,
Zhang Ziyin^1,2,
Wen Wei^1,2

1.
Environmental Meteorology Forecast Center of Beijing-Tianjin-Hebei, Beijing 100089
2.
Institute of Urban Meteorology, CMA, Beijing 100089
3.
Department of Environmental Sciences, College of Environmental Sciences and Engineering, Peking University, Beijing 100871

Received Date: 2016-03-22
Rev Recd Date: 2016-06-15
Publish Date: 2016-11-30

Abstract

Abstract

In recent years, the atmospheric environment in parts of China has become significantly degraded and the need for emission controlling has become urgent. As more international events have been carried out, and more serious pollution weather happens frequently, it is important to implement air quality assurance targeted at significant events held during specific periods. A representative pollution episode, 6 November to 11 November in 2014 is chosen and simulations are carried out setting urban area of Beijing as the target region. By using the method of footprint analysis, the sensitive source zones that have the greatest impact on the air quality of the Beijing urban area are determined. Regional chemical and transportation model WRF-Chem is used to establish emission reduction tests for the focus source zones and for specific sensitive source zones within and around Beijing. Results show that two kinds of tests have significant effects on PM_2.5 concentration decreasing in the emission reduction local with high intensity of emission source. Besides, the effect could also result in the decrease of pollutant concentration in downwind area under the transportation function. But only in terms of the target area, initiating a moderate emission reduction for specific sensitive source zones is more effective on the air quality of urban Beijing than initiating the same strength emission reduction for focus source zones. In certain cases when the PM_2.5 direct emission reduction for the specific sensitive source zones accounts for less than 20% of focus source zones, the PM_2.5 concentration reduction amount in Beijing urban area can reach the level when the sensitive source zones reduction scheme accounts for about 60%-90% of focus source zones. This ratio maintains stable through all pollution process. Thus the daily dynamical emission reduction measures developed based on the sensitive source zones analysis, can help cut the emission control costs and improve the emission reduction efficiency. In addition, results from different study cases in different pollution degree further prove the above conclusions, indicating the reliable applicability of the dynamical emission reduction scheme in the guidance of emission reduction measures. Therefore, when enacting emission reduction schemes, cooperating with surrounding provinces and cities, as well as narrowing the reduction scope to specific sensitive source zones prior to unfavorable meteorological conditions, can help reduce emission control costs and improve the efficiency and maneuverability of emission reduction schemes.
- footprint;
- sensitive source zones;
- emission reduction;
- numerical simulation

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References(31)

Figures and Tables

图 1 2014年10月1—11月13日北京地区AQI观测与模拟对比

(a) 相对误差, (b) AQI

Fig. 1 Variation of simulated and observed air quality index of Beijing area from 1 Otc to 13 Nov in 2014

(a) relative deviation, (b) AQI

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图 2 2014年11月7—10日20:00地面PM_2.5浓度模拟结果与观测对比

(色阶底图为模拟结果，实心圆点代表观测结果)

Fig. 2 Comparison of the surface PM_2.5 concentration between the simulated and the observed

(simulated and observed values are indicated by shaded base graphics and shaded circles, respectively)

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Fig. 3 Footprint from 7 Nov to 10 Nov in 2014

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图 4 华北区域PM_2.5排放强度分布

(单位:t·km^-2·d^-1)

Fig. 4 The distribution of PM_2.5 emission intensity of Huabei region

(unit:t·km^-2·d^-1)

DownLoad: Full-Size Img PowerPoint

图 5 各减排方案PM_2.5日排放量的削减量及削减比例

(柱状图:削减量; 点线图:削减比例)

Fig. 5 Reduction quantity and reduction ratio of daily PM_2.5 emissions for different emission-cut schemes

(bar:reduction quantity; line:reduction ratio)

DownLoad: Full-Size Img PowerPoint

Fig. 6 Spatial distribution of surface PM_2.5 concentration in Beijing and around areas from 7 Nov to 10 Nov in 2014 of base case

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Fig. 7 Spatial distribution of surface PM_2.5 concentration in Beijing and around areas from 7 Nov to 10 Nov in 2014 of focus source zones emission-cut case

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Fig. 8 Spatial distribution of surface PM_2.5 concentration in Beijing and around areas from 7 Nov to 10 Nov in 2014 of sensitive source zone emission-cut case

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Fig. 9 Reduction quantity of PM_2.5 daily concentration for target area simulated by different emission-cut schemes

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Table 1 Scheme design of different emission-cut regions

方案名称	方案设计	分析时段	减排物种
重点区域减排(C1)	北京及周边地区减排,减排区域为37.0°~42.0°N， 113.0°~119.0°E; 减排力度:人为源排放削减 50%
敏感区域减排1(C2)	根据逐日印痕分析结果，全部敏感源区人为源排放削减50%	2014-11-06—11	SO₂,NO_x, PM₁₀,PM_2.5, VOCs,NH₃
敏感区域减排1(C3)	根据逐日印痕分析结果，重要敏感源区人为源排放削减50%，比较重要敏感源区削减40%，一般敏感源区削减30%

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Table 2 Comparison of reduction efficiency of PM_2.5 concentration for different scheme in three cases

统计项目	2012-08-24—26 (基础浓度：156 μg·m^-3)			2013-10-31—11-02 (基础浓度：207 μg·m^-3)			2014-11-06—11 (基础浓度：97 μg·m^-3)
统计项目	方案C1	方案C2	比例/%	方案C1	方案C2	比例/%	方案C1	方案C2	比例/%
平均日排放削减量/(t·d^-1)	2300	360	16	2325	1120	48	2650	650	25
平均浓度削减量/(μg·m^-3)	29	21	72	98	84	88	36	25	70
平均浓度削减比例/%	19	14	72	47	41	88	37	26	70

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